The warpgroup algorithm takes detected peaks appearing across multiple LC/MS samples and determines: 1. The most appropriate segregation of those peaks using a local DTW alignment and graph decomposition; 2. Per-group consensus integration bounds such that each group represents a topographically similar region of the peak chromatogram; 3. The corresponding peak integration bounds for samples in which no peak was detected. Additionally the output provides effective parameters for filtering "good peaks" from "noise peaks".
|Author||Nathaniel Guy Mahieu <[email protected]>|
|Maintainer||Nathaniel Guy Mahieu <[email protected]>|
|Package repository||View on GitHub|
Install the latest version of this package by entering the following in R:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.